The role of realized ex-post covariance measures and dynamic model choice on the quality of covariance forecasts

Autor:	Rasmus T. Varneskov, Valeri Voev
Rok vydání:	2013
Předmět:	Estimation Economics and Econometrics media_common.quotation_subject Estimator Sampling (statistics) Covariance Measure (mathematics) Market risk Statistics Econometrics Economics Quality (business) Portfolio optimization Finance media_common
Zdroj:	Varneskov, R T & Voev, V R 2013, ' The role of realized ex-post covariance measures and dynamic model choice on the quality of covariance forecasts ', Journal of Empirical Finance, vol. 20, no. January, pp. 83-95 . https://doi.org/10.1016/j.jempfin.2012.11.002
ISSN:	0927-5398
DOI:	10.1016/j.jempfin.2012.11.002
Popis:	Recently, consistent measures of the ex-post covariation of financial assets based on noisy high-frequency data have been proposed. A related strand of literature focuses on dynamic models and covariance forecasting for high-frequency data based covariance measures. The aim of this paper is to investigate whether more sophisticated estimation approaches lead to more precise covariance forecasts, both in a statistical precision sense and in terms of economic value. A further issue, we address, is the relative importance of the quality of the realized measure as an input in a given forecasting model vs. the model's dynamic specification. The main finding is that the largest gains result from switching from daily to high-frequency data. Further gains are achieved if a simple sparse sampling covariance measure is replaced with a more efficient and noise-robust estimator.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db92c6ad7371f1606840d1096757cb0b https://doi.org/10.1016/j.jempfin.2012.11.002 Zobrazit plný text záznamu Full Text from ScienceDirect